Services Recommendation in Systems Based on Service Oriented Architecture by Applying Modified ROCK Algorithm. - Agnieszka Prusiewicz; Maciej Zieba (NDT (2), 2010)

Analysis of Human Arm Motions Recognition Algorithms for System to Visualize Virtual Arm. - Krzysztof Brzostowski; Maciej Zieba (ICSEng, 2011)

The Proposal of Service Oriented Data Mining System for Solving Real-Life Classification and Regression Problems. - Agnieszka Prusiewicz; Maciej Zieba (DoCEIS, 2011)

On some method for limited services selection. - Agnieszka Prusiewicz; Maciej Zieba (Int. J. Intell. Inf. Database Syst., 2011)

Ensemble Classifier for Solving Credit Scoring Problems. - Maciej Zieba; Jerzy Swiatek (DoCEIS, 2012)

Ensemble SVM for imbalanced data and missing values in postoperative risk management. - Maciej Zieba; Jerzy Swiatek (Healthcom, 2013)

Cost Sensitive SVM with Non-informative Examples Elimination for Imbalanced Postoperative Risk Management Problem. - Maciej Zieba; Jerzy Swiatek; Marek Lubicz (ICSS, 2013)

On-line bayesian context change detection in web service systems. - Jakub Mikolaj Tomczak; Maciej Zieba (HotTopiCS, 2013)

Selecting right questions with Restricted Boltzmann Machines. - Maciej Zieba; Jakub M. Tomczak; Krzysztof Brzostowski (ICSEng, 2014)

Boosted SVM for extracting rules from imbalanced data in application to prediction of the post-operative life expectancy in the lung cancer patients. - Maciej Zieba; Jakub M. Tomczak; Marek Lubicz; Jerzy Swiatek (Appl. Soft Comput., 2014)

RBM-SMOTE: Restricted Boltzmann Machines for Synthetic Minority Oversampling Technique. - Maciej Zieba; Jakub M. Tomczak; Adam Gonczarek (ACIIDS (1), 2015)

Classification Restricted Boltzmann Machine for comprehensible credit scoring model. - Jakub M. Tomczak; Maciej Zieba (Expert Syst. Appl., 2015)

Probabilistic combination of classification rules and its application to medical diagnosis. - Jakub M. Tomczak; Maciej Zieba (Mach. Learn., 2015)

Boosted SVM with active learning strategy for imbalanced data. - Maciej Zieba; Jakub M. Tomczak (Soft Comput., 2015)

Self-paced Learning for Imbalanced Data. - Maciej Zieba; Jakub M. Tomczak; Jerzy Swiatek (ACIIDS (1), 2016)

Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction. - Maciej Zieba; Sebastian K. Tomczak; Jakub M. Tomczak (Expert Syst. Appl., 2016)

Training Triplet Networks with GAN. - Maciej Zieba; Lei Wang 001 (ICLR (Workshop), 2017)

BinGAN: Learning Compact Binary Descriptors with a Regularized GAN. - Maciej Zieba; Piotr Semberecki; Tarek El-Gaaly; Tomasz Trzcinski (NeurIPS, 2018)

Gaussian process regression for automated signal tracking in step-wise perturbed Nuclear Magnetic Resonance spectra. - Maciej Zieba; Piotr Klukowski; Adam Gonczarek; Yaroslav Nikolaev; Michal J. Walczak (Appl. Soft Comput., 2018)

NMRNet: a deep learning approach to automated peak picking of protein NMR spectra. - Piotr Klukowski; Michal Augoff; Maciej Zieba; Maciej Drwal; Adam Gonczarek; Michal J. Walczak (Bioinform., 2018)

Adversarial Autoencoders for Generating 3D Point Clouds. - Maciej Zamorski; Maciej Zieba; Rafal Nowak; Wojciech Stokowiec; Tomasz Trzcinski (CoRR, 2018)

Semi-supervised Learning with Bidirectional GANs. - Maciej Zamorski; Maciej Zieba (ACIIDS (1), 2019)

Generative Adversarial Networks: Recent Developments. - Maciej Zamorski; Adrian Zdobylak; Maciej Zieba; Jerzy Swiatek (ICAISC (1), 2019)

Conditional Invertible Flow for Point Cloud Generation. - Michal Stypulkowski; Maciej Zamorski; Maciej Zieba; Jan Chorowski (CoRR, 2019)

Post-training Quantization Methods for Deep Learning Models. - Piotr Kluska; Maciej Zieba (ACIIDS (1), 2020)

Comparison of Aggregation Functions for 3D Point Clouds Classification. - Maciej Zamorski; Maciej Zieba; Jerzy Swiatek (ACIIDS (1), 2020)

Semi-supervised Representation Learning for 3D Point Clouds. - Adrian Zdobylak; Maciej Zieba (ACIIDS (1), 2020)

Generative Modeling in Application to Point Cloud Completion. - Maciej Zamorski; Maciej Zieba; Jerzy Swiatek (ICAISC (1), 2020)

Hypernetwork approach to generating point clouds. - Przemyslaw Spurek; Sebastian Winczowski; Jacek Tabor; Maciej Zamorski; Maciej Zieba; Tomasz Trzcinski (ICML, 2020)

UCSG-NET- Unsupervised Discovering of Constructive Solid Geometry Tree. - Kacper Kania; Maciej Zieba; Tomasz Kajdanowicz (NeurIPS, 2020)

HyperFlow: Representing 3D Objects as Surfaces. - Przemyslaw Spurek; Maciej Zieba; Jacek Tabor; Tomasz Trzcinski (CoRR, 2020)

Adversarial autoencoders for compact representations of 3D point clouds. - Maciej Zamorski; Maciej Zieba; Piotr Klukowski; Rafal Nowak; Karol Kurach; Wojciech Stokowiec; Tomasz Trzcinski (Comput. Vis. Image Underst., 2020)

Non-Gaussian Gaussian Processes for Few-Shot Regression. - Marcin Sendera; Jacek Tabor; Aleksandra Nowak 001; Andrzej Bedychaj; Massimiliano Patacchiola; Tomasz Trzcinski; Przemyslaw Spurek; Maciej Zieba (NeurIPS, 2021)

Modeling 3D Surface Manifolds with a Locally Conditioned Atlas. - Przemyslaw Spurek; Sebastian Winczowski; Maciej Zieba; Tomasz Trzcinski; Kacper Kania (CoRR, 2021)

Representing point clouds with generative conditional invertible flow networks. - Michal Stypulkowski; Kacper Kania; Maciej Zamorski; Maciej Zieba; Tomasz Trzcinski; Jan Chorowski (Pattern Recognit. Lett., 2021)

PluGeN: Multi-Label Conditional Generation from Pre-trained Models. - Maciej Wolczyk; Magdalena Proszewska; Lukasz Maziarka; Maciej Zieba; Patryk Wielopolski; Rafal Kurczab; Marek Smieja (AAAI, 2022)

Eigenvector Grouping for Point Cloud Vessel Labeling. - Patryk Rygiel; Maciej Zieba; Tomasz K. Konopczynski (GeoMedIA, 2022)

FlowHMM: Flow-based continuous hidden Markov models. - Pawel Lorek; Rafal Nowak; Tomasz Trzcinski; Maciej Zieba (NeurIPS, 2022)

HyperMAML: Few-Shot Adaptation of Deep Models with Hypernetworks. - Marcin Przewiezlikowski; P. Przybysz; Jacek Tabor; Maciej Zieba; Przemyslaw Spurek (CoRR, 2022)

TreeFlow: Going beyond Tree-based Gaussian Probabilistic Regression. - Patryk Wielopolski; Maciej Zieba (CoRR, 2022)

Two-headed eye-segmentation approach for biometric identification. - Wiktor Lazarski; Maciej Zieba; Tanguy Jeanneau; Tobias Zillig; Christian Brendel (CoRR, 2022)

General Hypernetwork Framework for Creating 3D Point Clouds. - Przemyslaw Spurek; Maciej Zieba; Jacek Tabor; Tomasz Trzcinski (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Flow Plugin Network for Conditional Generation. - Patryk Wielopolski; Michal Koperski; Maciej Zieba (ACIIDS (2), 2023)

Classical Out-of-Distribution Detection Methods Benchmark in Text Classification Tasks. - Mateusz Baran; Joanna Baran; Mateusz Wójcik; Maciej Zieba; Adam Gonczarek (ACL (student), 2023)

TreeFlow: Going Beyond Tree-Based Parametric Probabilistic Regression. - Patryk Wielopolski; Maciej Zieba (ECAI, 2023)

Modeling Uncertainty in Personalized Emotion Prediction with Normalizing Flows. - Piotr Milkowski; Konrad Karanowski; Patryk Wielopolski; Jan Kocon; Przemyslaw Kazienko; Maciej Zieba (ICDM (Workshops), 2023)

CenterlinePointNet++: A New Point Cloud Based Architecture for Coronary Artery Pressure Drop and vFFR Estimation. - Patryk Rygiel; Pawel Pluszka; Maciej Zieba; Tomasz K. Konopczynski (MICCAI (7), 2023)

HyperShot: Few-Shot Learning by Kernel HyperNetworks. - Marcin Sendera; Marcin Przewiezlikowski; Konrad Karanowski; Maciej Zieba; Jacek Tabor; Przemyslaw Spurek (WACV, 2023)

Generic projections of the H4 configuration of points. - Paulina Wisniewska; Maciej Zieba (Adv. Appl. Math., 2023)

HyperNeRFGAN: Hypernetwork approach to 3D NeRF GAN. - Adam Kania; Artur Kasymov; Maciej Zieba; Przemyslaw Spurek (CoRR, 2023)

NeRFlame: FLAME-based conditioning of NeRF for 3D face rendering. - Wojciech Zajac; Jacek Tabor; Maciej Zieba; Przemyslaw Spurek (CoRR, 2023)

MultiPlaneNeRF: Neural Radiance Field with Non-Trainable Representation. - Dominik Zimny; Jacek Tabor; Maciej Zieba; Przemyslaw Spurek (CoRR, 2023)

Continual learning on 3D point clouds with random compressed rehearsal. - Maciej Zamorski; Michal Stypulkowski; Konrad Karanowski; Tomasz Trzcinski; Maciej Zieba (Comput. Vis. Image Underst., 2023)

The general framework for few-shot learning by kernel HyperNetworks. - Marcin Sendera; Marcin Przewiezlikowski; Jan Miksa; Mateusz Rajski; Konrad Karanowski; Maciej Zieba; Jacek Tabor; Przemyslaw Spurek (Mach. Vis. Appl., 2023)

Self-supervised Adversarial Masking for 3D Point Cloud Representation Learning. - Michal Szachniewicz; Wojciech Kozlowski; Michal Stypulkowski; Maciej Zieba (ACIIDS (2), 2024)

RegFlow: Probabilistic Flow-Based Regression for Future Prediction. - Maciej Zieba; Marcin Przewiezlikowski; Marek Smieja; Jacek Tabor; Tomasz Trzcinski; Przemyslaw Spurek (ACIIDS (Companion 2), 2024)

Probabilistically Plausible Counterfactual Explanations with Normalizing Flows. - Patryk Wielopolski; Oleksii Furman; Jerzy Stefanowski; Maciej Zieba (ECAI, 2024)

Modeling 3D Surfaces with a Locally Conditioned Atlas. - Przemyslaw Spurek; Sebastian Winczowski; Maciej Zieba; Tomasz Trzcinski; Kacper Kania; Marcin Mazur (ICCS (2), 2024)

NeRFlame: Flame-Based Conditioning of NeRF for 3D Face Rendering. - Wojciech Zajac; Joanna Waczynska; Piotr Borycki; Jacek Tabor; Maciej Zieba; Przemyslaw Spurek (ICCS (1), 2024)

A Comparative Analysis of Siamese Networks and Spectral Angle Mapper for Mineral Detection using Hyperspectral Imagery. - Katarzyna Jablonska; Maciej Zieba (IGARSS, 2024)

Diffused Heads: Diffusion Models Beat GANs on Talking-Face Generation. - Michal Stypulkowski; Konstantinos Vougioukas; Sen He 001; Maciej Zieba; Stavros Petridis; Maja Pantic (WACV, 2024)

Unifying Perspectives: Plausible Counterfactual Explanations on Global, Group-wise, and Local Levels. - Patryk Wielopolski; Oleksii Furman; Jerzy Stefanowski; Maciej Zieba (CoRR, 2024)

AutoLoRA: AutoGuidance Meets Low-Rank Adaptation for Diffusion Models. - Artur Kasymov; Marcin Sendera; Michal Stypulkowski; Maciej Zieba; Przemyslaw Spurek (CoRR, 2024)

Neural Surface Priors for Editable Gaussian Splatting. - Jakub Szymkowiak; Weronika Jakubowska; Dawid Malarz; Weronika Smolak-Dyzewska; Maciej Zieba; Przemyslaw Musialski; Wojtek Palubicki; Przemyslaw Spurek (CoRR, 2024)

Speech driven video editing via an audio-conditioned diffusion model. - Dan Bigioi; Shubhajit Basak; Michal Stypulkowski; Maciej Zieba; Hugh Jordan; Rachel McDonnell; Peter Corcoran 001 (Image Vis. Comput., 2024)

MineCam: Application of Combined Remote Sensing and Machine Learning for Segmentation and Change Detection of Mining Areas Enabling Multi-Purpose Monitoring. - Katarzyna Jablonska; Marcin Maksymowicz; Dariusz Tanajewski; Wojciech Kaczan; Maciej Zieba; Marek Wilgucki (Remote. Sens., 2024)

NodeFlow: Towards End-to-End Flexible Probabilistic Regression on Tabular Data. - Patryk Wielopolski; Oleksii Furman; Maciej Zieba (Entropy, 2024)

Dimma: Semi-Supervised Low-Light Image Enhancement with Adaptive Dimming. - Wojciech Kozlowski; Michal Szachniewicz; Michal Stypulkowski; Maciej Zieba (Entropy, 2024)

Multi-Label Conditional Generation From Pre-Trained Models. - Magdalena Proszewska; Maciej Wolczyk; Maciej Zieba; Patryk Wielopolski; Lukasz Maziarka; Marek Smieja (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Image Enhancement with Boosted Schrödinger Bridge. - Wojciech Kozlowski; Radoslaw Kuczbanski; Maciej Zieba (ACIIDS (2), 2025)

KeyFace: Expressive Audio-Driven Facial Animation for Long Sequences via KeyFrame Interpolation. - Antoni Bigata Casademunt; Michal Stypulkowski; Rodrigo Mira; Stella Bounareli; Konstantinos Vougioukas; Zoe Landgraf; Nikita Drobyshev; Maciej Zieba; Stavros Petridis; Maja Pantic (CVPR, 2025)

SupResDiffGAN a New Approach for the Super-Resolution Task. - Dawid Kopec; Wojciech Kozlowski; Maciej Wizerkaniuk; Dawid Krutul; Jan Kocon; Maciej Zieba (ICCS (Workshops 3), 2025)

Hypernetworks for image recontextualization. - Maciej Zieba; Jakub Balicki; Tomasz Drózdz; Konrad Karanowski; Pawel Lorek; Hong Lyu; Aleksander Skorupa; Tomasz Trzcinski; Oriol Caudevilla; Jakub M. Tomczak (UniReps, 2025)

Amodal Instance Segmentation for Mealworm Growth Monitoring Using Synthetic Training Images. - Przemyslaw Dolata; Pawel Majewski; Piotr Lampa; Maciej Zieba; Jacek Reiner (IEEE Access, 2025)

MultiPlaneNeRF: Neural radiance field with non-trainable representation. - Dominik Zimny; Artur Kasymov; Adam Kania; Jacek Tabor; Maciej Zieba; Marcin Mazur; Przemyslaw Spurek (Expert Syst. Appl., 2025)

Classifier-free Guidance with Adaptive Scaling. - Dawid Malarz; Artur Kasymov; Maciej Zieba; Jacek Tabor; Przemyslaw Spurek (CoRR, 2025)

DiCoFlex: Model-agnostic diverse counterfactuals with flexible control. - Oleksii Furman; Ulvi Movsum-zada; Patryk Marszalek; Maciej Zieba; Marek Smieja (CoRR, 2025)